Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System

Aye Than Mon; Su Mon Aye; Hla Myo Tun; Zaw Min Naing; Win Khaing Moe

doi:doi:10.11648/j.se.20180602.12

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Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System

Aye Than Mon, Su Mon Aye, Hla Myo Tun, Zaw Min Naing, Win Khaing Moe

Published in Software Engineering (Volume 6, Issue 2)

Received: 23 June 2018 Accepted: 5 July 2018 Published: 2 August 2018

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Abstract

This research aims to design and implement of tree-structured multichannel filter banks using MATLAB. The multichannel filter banks analysis are evaluated by the Digital Signal Processing (DSP) techniques. The multi rate analysis is suitable for sampling rate reduction and sampling rate increase on the digital filter design. When increasing sampling rate, filtering follows the up-sampling operation. The role of the filter is to attenuate unwanted periodic spectra which appear in the new baseband. The performance evaluation for tree-structured multichannel filter banks design is described in this research work. The experimental results for implemented design are implemented in this paper. The use of an appropriate filter enables one to convert a digital signal of a specified sampling rate into another signal with a target sampling rate without destroying the signal components of interest. The performance of multirate filtering for implemented design is evaluated by using MATLAB.

Published in	Software Engineering (Volume 6, Issue 2)
DOI	10.11648/j.se.20180602.12
Page(s)	37-46
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

DSP, Tree-Structured Multichannel Filter Banks, MATLAB, Digital Filter Design, Multirate Techniques

References

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[3]	Milić, L. D., & Lutovac, M. D. (2003). Efficient algorithm for the design of high-speed elliptic IIR filters. AEÜ Int. J. Electron. Commun, 57(4), 255-262.
[4]	Ansari, R., & Liu, B., (1993). Multirate signal processing. In Sanjit. K. Mitra and James F. Kaiser (ed.), Handbook for Digital Signal Processing. New York: John Wiley-Interscience, 981-1084.
[5]	Filter design toolbox for use with MATLAB. User’s guide. Version 6. (2006). Natick: MathWorks.
[6]	Fliege, N. J. (1994). Multirate digital signal processing. New York, NY: John Wiley.
[7]	Johnston, J. D. (March 1980). A filter family designed for use in quadrature mirror filter banks. Proceedings of the IEEE International Conference Acoustics, Speech, and Signal Processing, 291–294.
[8]	Mitra, S. K. (2006). Digital signal processing: A computer based approach. 3rd edition. New York, NY: The McGraw-Hill Companies, Inc.
[9]	Saramäki, T. Multirate Signal Processing. (2001). Lecture notes for a graduate course, the Institute of Signal Processing, Tampere University of Technology, Finland.
[10]	Saramäki, T., & Bregovic, R. (2002). Multirate systems and filter banks. In Gordana Jovanović-Doleček, (ed.), Multirate Systems: Design & Applications. Hershey, PA: Idea Group Publishing, 27-85.
[11]	Signal processing toolbox for use with MATLAB. User’s guide. Version 6. (2006). Natick: Math-Works.
[12]	Strang, G., & Nguyen, T. (1996). Wavelets and Filter Banks. Wellesley, MA: Wellesley-Cambridge Press.
[13]	Vaidyanathan, P. P. (1987). Quadrature mirror filter banks, M-band extensions and perfect-reconstruction techniques. IEEE ASSP Magazine, 4(3), 4-20.
[14]	Vaidyanathan, P. P. (1993). Multirate systems and filter banks. Englewood Cliffs, NJ: Prentice Hall.
[15]	Wavelet toolbox for use with MATLAB. User’s guide. Version 3. (2006). Natick: MathWorks.
[16]	Vetterli, M., & Kovačević, J.(1995). Wavelets and Subband Codding. Englewood Cliffs, N. J.: Prentice Hall.
[17]	Yue-Dar Jou. (May 2007). Design of two-channel linear-phase quadrature mirror filter banks based on neural networks. Signal Processing, 87(5), 1031-1044.
[18]	S. Dimitrov, “Non-linear distortion noise cancellation for satellite forward links,” in Proc. 8th Advanced Satellite Multimedia Systems Conference (ASMS2016), Palma de Mallorca, Spain, Sep. 5-7 2016.
[19]	S. Dimitrov, “Iterative cancellation of non-linear distortion noise in digital communication systems,” IEEE Trans. Commun., vol. 63, no. 6, pp. 2325–2336, Jun. 2015.
[20]	Implementation Guidelines for the Second Generation System for Broadcasting, Interactive Services, News Gathering and Other Broadband Satellite Applications; Part II: S2-Extensions (DVB-S2X), Digital Video Broadcasting (DVB) Std. ETSI TR 102 376-2, Mar. 2015.

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APA Style

Aye Than Mon, Su Mon Aye, Hla Myo Tun, Zaw Min Naing, Win Khaing Moe. (2018). Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System. Software Engineering, 6(2), 37-46. https://doi.org/10.11648/j.se.20180602.12

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ACS Style

Aye Than Mon; Su Mon Aye; Hla Myo Tun; Zaw Min Naing; Win Khaing Moe. Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System. Softw. Eng. 2018, 6(2), 37-46. doi: 10.11648/j.se.20180602.12

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AMA Style

Aye Than Mon, Su Mon Aye, Hla Myo Tun, Zaw Min Naing, Win Khaing Moe. Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System. Softw Eng. 2018;6(2):37-46. doi: 10.11648/j.se.20180602.12

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@article{10.11648/j.se.20180602.12,
  author = {Aye Than Mon and Su Mon Aye and Hla Myo Tun and Zaw Min Naing and Win Khaing Moe},
  title = {Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System},
  journal = {Software Engineering},
  volume = {6},
  number = {2},
  pages = {37-46},
  doi = {10.11648/j.se.20180602.12},
  url = {https://doi.org/10.11648/j.se.20180602.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.se.20180602.12},
  abstract = {This research aims to design and implement of tree-structured multichannel filter banks using MATLAB. The multichannel filter banks analysis are evaluated by the Digital Signal Processing (DSP) techniques. The multi rate analysis is suitable for sampling rate reduction and sampling rate increase on the digital filter design. When increasing sampling rate, filtering follows the up-sampling operation. The role of the filter is to attenuate unwanted periodic spectra which appear in the new baseband. The performance evaluation for tree-structured multichannel filter banks design is described in this research work. The experimental results for implemented design are implemented in this paper. The use of an appropriate filter enables one to convert a digital signal of a specified sampling rate into another signal with a target sampling rate without destroying the signal components of interest. The performance of multirate filtering for implemented design is evaluated by using MATLAB.},
 year = {2018}
}

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TY - JOUR
T1 - Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System
AU - Aye Than Mon
AU - Su Mon Aye
AU - Hla Myo Tun
AU - Zaw Min Naing
AU - Win Khaing Moe
Y1 - 2018/08/02
PY - 2018
N1 - https://doi.org/10.11648/j.se.20180602.12
DO - 10.11648/j.se.20180602.12
T2 - Software Engineering
JF - Software Engineering
JO - Software Engineering
SP - 37
EP - 46
PB - Science Publishing Group
SN - 2376-8037
UR - https://doi.org/10.11648/j.se.20180602.12
AB - This research aims to design and implement of tree-structured multichannel filter banks using MATLAB. The multichannel filter banks analysis are evaluated by the Digital Signal Processing (DSP) techniques. The multi rate analysis is suitable for sampling rate reduction and sampling rate increase on the digital filter design. When increasing sampling rate, filtering follows the up-sampling operation. The role of the filter is to attenuate unwanted periodic spectra which appear in the new baseband. The performance evaluation for tree-structured multichannel filter banks design is described in this research work. The experimental results for implemented design are implemented in this paper. The use of an appropriate filter enables one to convert a digital signal of a specified sampling rate into another signal with a target sampling rate without destroying the signal components of interest. The performance of multirate filtering for implemented design is evaluated by using MATLAB.
VL - 6
IS - 2
ER -

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Author Information

Aye Than Mon

Department of Electronic Engineering, Technological University (Pathein), Pathein, Myanmar
Su Mon Aye

Department of Electronic Engineering, Technological University (Pathein), Pathein, Myanmar
Hla Myo Tun

Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Zaw Min Naing

Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Win Khaing Moe

Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar

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Plain Text BibTeX RIS

APA Style

Aye Than Mon, Su Mon Aye, Hla Myo Tun, Zaw Min Naing, Win Khaing Moe. (2018). Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System. Software Engineering, 6(2), 37-46. https://doi.org/10.11648/j.se.20180602.12

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ACS Style

Aye Than Mon; Su Mon Aye; Hla Myo Tun; Zaw Min Naing; Win Khaing Moe. Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System. Softw. Eng. 2018, 6(2), 37-46. doi: 10.11648/j.se.20180602.12

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AMA Style

Aye Than Mon, Su Mon Aye, Hla Myo Tun, Zaw Min Naing, Win Khaing Moe. Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System. Softw Eng. 2018;6(2):37-46. doi: 10.11648/j.se.20180602.12

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@article{10.11648/j.se.20180602.12,
  author = {Aye Than Mon and Su Mon Aye and Hla Myo Tun and Zaw Min Naing and Win Khaing Moe},
  title = {Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System},
  journal = {Software Engineering},
  volume = {6},
  number = {2},
  pages = {37-46},
  doi = {10.11648/j.se.20180602.12},
  url = {https://doi.org/10.11648/j.se.20180602.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.se.20180602.12},
  abstract = {This research aims to design and implement of tree-structured multichannel filter banks using MATLAB. The multichannel filter banks analysis are evaluated by the Digital Signal Processing (DSP) techniques. The multi rate analysis is suitable for sampling rate reduction and sampling rate increase on the digital filter design. When increasing sampling rate, filtering follows the up-sampling operation. The role of the filter is to attenuate unwanted periodic spectra which appear in the new baseband. The performance evaluation for tree-structured multichannel filter banks design is described in this research work. The experimental results for implemented design are implemented in this paper. The use of an appropriate filter enables one to convert a digital signal of a specified sampling rate into another signal with a target sampling rate without destroying the signal components of interest. The performance of multirate filtering for implemented design is evaluated by using MATLAB.},
 year = {2018}
}

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